A system of C language programs has been developed for the purpose of finding the closely related documents in Medline. The system has a number of unique features: 1) It is highly modular so that alterations in the system are relatively simple to perform. 2) The system currently operates on Medline data in the ASN1 format but a change in the interface portion of the system would allow it to be applied to any large database consisting of discrete textual records. 3) The system is designed with a degree of security against loss of data due to operating system crashes or power outages. 4) All data processed by the system is stored in permanent form as inverted file structures, etc. These structures are updatable so that new data may be continually added to the system as it becomes available. 5) Documents are compared with each other using a Bayesian form of analysis and the statistics on which the relevance weighting of terms is based are derived from previous document comparisons. These statistics are updated with each new cycle of processing. The latest work on this system has involved developing a method to correct the scores of short documents. Short documents tend to score artificially high against other short documents and this leads to incorrect retrieval. A formula has been worked out to correct for this anomally and it has been implemented.